Building predictive models within interactive business analysis processes
View Patent ↗A Customer Relationship Management (CRM) system that dynamically builds predictive models. The system is used by business users who are unfamiliar with the art of data mining. A model-building mechanism in a data mining subsystem is presented with a training segment consisting of records with appropriate input attributes and an output attribute to be predicted; the model-building mechanism builds a model in the form of a business measure that can subsequently be applied to make predictions against other like segments.
1. A method for dynamically building predictive models within a computer-implemented business analysis environment, comprising:
(a) generating a definition for a derived measure;
(b) invoking a model-building mechanism in a data mining system based on the generated definition, wherein the model-building mechanism builds a predictive model that generates an output for the derived measure.
2. The method of claim 1 , further comprising applying the derived measure against a segment by executing the predictive model, and generating an output for the segment from the predictive model.
3. The method of claim 1 , wherein the derived measure is defined within an application template, the application template comprises a sequence of elements linked together in a workflow, and the elements Are selected from a group comprising a segment, a filter, a measure and a function.
4. The method of claim 3 , wherein the application template is constructed in a visual programming environment.
5. The method of claim 4 , wherein the application templates can be reused for modified by users.
6. The method of claim 3 , wherein in the segment is a grouping of data elements from a database organized about one or more attributes.
7. The method of claim 3 , wherein the filter defines one or more attribute constraints applied to a segment.
8. The method of claim 3 , wherein the profile is a labeled collection of attributes of a segment.
9. The method of claim 3 , wherein the measure is an expression applied to a segment.
10. The method of claim 3 , wherein the computer-implemented business analysis environment includes an object model, ad the segments, attributes, filters, and measures comprise objects.
11. The method of claim 10 , wherein operations upon the objects are translated into SQL statements that access corresponding tables and columns in a relational database.
12. The method of claim 1 , wherein the predictive model comprises one or more SQL statements that access tables and columns in a relational database.
13. The method of claim 1 , wherein the predictive model comprises one or more statements executed by a database management system.
14. The method of claim 13 , wherein the statements access data stored in the database management system.
15. The method of claim 1 , wherein the model-building mechanism comprises an analytic algorithm for rule induction performed against data stored in a database segment system to create the predictive model.
16. A computer-implemented system for dynamically building predictive models, comprising:
(a) logic, performed by a computer; for generating a definition for a derived measure; and
(b) logic, performed by a computer; for invoking a model-building mechanism in a dart mining system based on the generated definition, wherein the model-building mechanism builds a predictive model that generates an output for the derived measure.
17. The system of claim 16 , further comprising logic for applying the derived measure against a segment by executing the predictive model, and generating an output for the segment from the predictive model.
18. The system of claim 16 , wherein the derived measure is defined within an application template, the application template comprises a sequence of elements linked together in a workflow, and the elements are selected from a group comprising a segment, a filter, a measure and a function.
19. The system of claim 18 , wherein the application template is constructed in a visual programming environment.
20. The system of claim 19 , wherein the application templates can be reused or modified by users.
21. The system of claim 18 , wherein the segment is a grouping of data elements from a database organized about one or more attributes.
22. The system of claim 18 , wherein the filter defines one or more attribute constraints applied to a segment.
23. The system of claim 18 , wherein has profile is a labeled collection of attributes of a segment.
24. The system of claim 18 , wherein the measure is an expression applied to a segment.
25. The system of claim 18 , wherein the computer-implemented business analysis environment includes an object model, and the segments, attributes, filters, and measures comprise objects.
26. The system of claim 25 , wherein operations upon the objects are translated into SQL statements that access corresponding tables and columns in a relational database.
27. The system of claim 16 , wherein the predictive model comprises one or more SQL statements that access tables and columns in a relational database.
28. The system of claim 16 , wherein the predictive model comprises one or more statements executed by a database management system.
29. The system of claim 28 , wherein the statements access data stored in the database management system.
30. The system of claim 16 , wherein the model-building mechanist comprises an analytic algorithm for role induction performed against data stored in a database management system to create the predictive model.
31. An article of manufacture embodying logic for dynamically building predictive models within a computer-implemented business analysis environment, the logic comprising:
(a) generating a definition for a derived measure;
(b) invoking a model-building mechanism in a data mining system based on the generated definition, wherein the model-building mechanism builds a predictive model that generates an output for the derived measure.
32. The article of manufacture of claim 31 , further comprising applying the derived measure against a segment by executing the predictive model, and generating an output for the segment from the predictive model.
33. The article of manufacture of claim 31 , wherein the derived measure is defined within an application template, the application template comprises a sequence of elements linked together in a workflow, and the elements are selected from a group comprising a segment, a filter, a measure and a function.
34. The article of manufacture of claim 33 , wherein the application template is constructed in a visual programming environment.
35. The article of manufacture of claim 34 , wherein the application templates can be reused or modified by users.
36. The article of manufacture of claim 33 , wherein the segment is a grouping of data elements from a database organized about one or more attributes.
37. The article of manufacture of claim 33 , wherein the filter defines one or more attribute constraints applied to a segment.
38. The article of manufacture of claim 33 , wherein the profile is a labeled collection of attributes of a segment.
39. The article of manufacture of claim 33 , wherein the measure is an expression applied to a segment.
40. The article of manufacture of claim 33 , wherein the computer-implemented business analysis environment includes an object model and the segments, attributes, filters, and measures comprise objects.
41. The article of manufacture of claim 40 , wherein operations upon the objects are translated into SQL statements that access corresponding tables and columns in a relational database.
42. The article of manufacture of claim 31 , wherein the predictive model comprises one or more SQL statements that access tables and columns in a relational database.
43. The article of manufacture of claim 31 , wherein the predictive model comprises one or more statements executed by a database management system.
44. The article of manufacture of claim 43 , wherein the statements access data stored in the database management system.
45. The article of manufacture of claim 31 , wherein the model-building mechanism comprises an analytic algorithm for rule induction performed against data stored in a database management system to create the predictive model.